Australian perspectives on artificial intelligence in medical imaging.

INTRODUCTION: While artificial intelligence (AI) and recent developments in deep learning (DL) have sparked interest in medical imaging, there has been little commentary on the impact of AI on imaging technologists. The aim of this survey was to understand the attitudes, applications and concerns among nuclear medicine and radiography professionals in Australia with regard to the rapidly emerging applications of AI. METHODS: An anonymous online survey with invitation to participate was circulated to nuclear medicine and radiography members of the Rural Alliance in Nuclear Scintigraphy and the Australian Society of Medical Imaging and Radiation Therapy. The survey invitations were sent to members via email and as a push via social media with the survey open for 10 weeks. All information collected was anonymised and there is no disclosure of personal information as it was de-identified from commencement. RESULTS: Among the 102 respondents, there was a high level of acceptance of lower order tasks (e.g. patient registration, triaging and dispensing) and less acceptance of high order task automation (e.g. surgery and interpretation). There was a low priority perception for the role of AI in higher order tasks (e.g. diagnosis, interpretation and decision making) and high priority for those applications that automate complex tasks (e.g. quantitation, segmentation, reconstruction) or improve image quality (e.g. dose / noise reduction and pseudo CT for attenuation correction). Medico-legal, ethical, diversity and privacy issues posed moderate or high concern while there appeared to be no concern regarding AI being clinically useful and improving efficiency. Mild concerns included redundancy, training bias, transparency and validity. CONCLUSION: Australian nuclear medicine technologists and radiographers recognise important applications of AI for assisting with repetitive tasks, performing less complex tasks and enhancing the quality of outputs in medical imaging. There are concerns relating to ethical aspects of algorithm development and implementation.

Imaging individuals with obesity.

Medical imaging is integral to the diagnosis and management of the co-morbidities associated with obesity. While individuals with obesity are increasingly imaged within Medical Radiation Science practice, identifying and understanding the challenges of imaging patients with obesity is an essential requirement for all Medical Radiation Practitioners (MRPs). This Continuing Professional Development article introduces key concepts related to imaging this patient group, explores technical considerations and system limitations within planar radiography, computed tomography (CT), nuclear medicine (NM), magnetic resonance imaging (MRI) and ultrasound (US) and explores patient centred care considerations when imaging patients with obesity.

Development of a professional competency framework for Australian sonographers-perspectives for developing competencies using a Delphi methodology.

BACKGROUND: Professional competencies are important for enhancing alignment between the needs of education, industry and health consumers, whilst describing public expectations around health professionals. The development of competency standards for the sonography profession defines the behaviours, skills and knowledge sonographers should demonstrate for each learning and experience level. OBJECTIVE: The objective of this project was to develop a set of professional competency standards for the sonography profession which described in depth the behaviours, skills and knowledge sonographers should demonstrate across multiple learning and experience levels. METHODS: Representatives of three Australian ultrasound professional associations and seven tertiary institutions involved in entry-level sonographer education in Australia formed a research team (RT). The RT recruited an expert panel that responded to six survey rounds. Using a Delphi methodology, the results and free-text comments from each previous round were fed back to participants in the subsequent survey rounds to achieve a consensus. RESULTS: The project developed a professional competency framework for sonographers, which included four major domains: detailed competency standards, sonographer knowledge, sonographer attitudes and a holistic competency matrix [https://doi.org/10.6084/m9.figshare.17148035.v2.]. CONCLUSION: The Delphi methodology is an effective way to develop professional competency standards. This paper describes the methods and challenges in developing such standards for sonographers which could be translated to other health professionals.

COVID-19 impact on undergraduate teaching: Medical radiation science teaching team experience.

The COVID-19 crisis has caused a number of significant challenges to the higher education sector. Universities worldwide have been forced to rapidly transition to online delivery, working at home, and disruption to research while concurrently facing the longer-term impacts in institution financial reform. Here, the impact of COVID-19 on academic staff in the medical radiation science (MRS) teaching team at Charles Sturt University are explored. While COVID-19 imposes potentially the greatest challenge many of us will experience in our personal and professional lifetimes, it also affords the opportunity to objectively re-evaluate and, where appropriate, re-design learning and teaching in higher education. Technology has allowed rapid assimilation to online learning environments with additional benefits that allow flexible, mobile, agile, sustainable, culturally safe and equitable learning focussed educational environments in the post-COVID-19 "new normal".